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» Abstraction in Predictive State Representations
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ICMLA
2010
14 years 7 months ago
Incremental Learning of Relational Action Rules
Abstract--In the Relational Reinforcement learning framework, we propose an algorithm that learns an action model allowing to predict the resulting state of each action in any give...
Christophe Rodrigues, Pierre Gérard, C&eacu...
CAISE
2011
Springer
14 years 1 months ago
Supporting Dynamic, People-Driven Processes through Self-learning of Message Flows
Abstract. Flexibility and automatic learning are key aspects to support users in dynamic business environments such as value chains across SMEs or when organizing a large event. Pr...
Christoph Dorn, Schahram Dustdar
ISI
2007
Springer
15 years 4 months ago
Making Sense of VAST Data
: We view the task of sensemaking in intelligence as that of abducing a story whose plot explains the current data and makes verifiable predictions about the future and the past. W...
Summer Adams, Ashok K. Goel
IPSN
2004
Springer
15 years 3 months ago
Distributed particle filters for sensor networks
Abstract. This paper describes two methodologies for performing distributed particle filtering in a sensor network. It considers the scenario in which a set of sensor nodes make m...
Mark Coates
TACAS
2001
Springer
119views Algorithms» more  TACAS 2001»
15 years 2 months ago
Compositional Message Sequence Charts
Abstract. A message sequence chart (MSC) is a standard notation for describing the interaction between communicating objects. It is popular among the designers of communication pro...
Elsa L. Gunter, Anca Muscholl, Doron Peled